A hybrid breast cancer detection system via neural network and feature selection based on SBS, SFS and PCA.
Mustafa Serter UzerOnur InanNihat YilmazPublished in: Neural Comput. Appl. (2013)
Keyphrases
- neural network
- breast cancer detection
- feature selection
- principal component analysis
- dimensionality reduction
- feature extraction
- feature space
- sparse pca
- dimension reduction
- stepwise regression
- hybrid intelligent
- x ray
- breast cancer
- feature reduction
- shape from shading
- principal components analysis
- pattern recognition
- artificial neural networks
- early stage
- mutual information
- face recognition
- prediction model
- light source
- support vector
- classification accuracy
- low dimensional
- back propagation
- machine learning
- feature subspace
- principle component analysis
- fuzzy neural network
- text classification
- text categorization
- neural network model
- perspective projection
- covariance matrix
- high dimensionality
- support vector machine
- independent component analysis
- feature selection algorithms
- information gain
- fuzzy logic
- feature set
- feature subset
- principal components
- k nearest neighbor
- high dimensional
- feature selection and classification
- image segmentation
- naive bayes